Language Processing Problems

Blending theoretical results with practical applications, this book provides an introduction to random matrix theory and shows how it can be used to tackle a variety of problems in wireless communications. The Stieltjes transform method, free probability theory, combinatoric approaches, deterministic equivalents and spectral analysis methods for statistical inference are all covered from a unique engineering perspective. Detailed mathematical derivations are presented throughout, with thorough explanation of the key results and all fundamental lemmas required for the reader to derive similar calculus on their own. These core theoretical concepts are then applied to a wide range of real-world problems in signal processing and wireless communications, including performance analysis of CDMA, MIMO and multi-cell networks, as well as signal detection and estimation in cognitive radio networks. The rigorous yet intuitive style helps demonstrate to students and researchers alike how to choose

Get up to speed with digital holography with this concise and straightforward introduction to modern techniques and conventions. Building up from the basic principles of optics, this book describes key techniques in digital holography, such as phase-shifting holography, low-coherence holography, diffraction tomographic holography and optical scanning holography, discussing their practical applications, and accompanied by all the theory necessary to understand the underlying principles at work. A further chapter covers advanced techniques for producing computer-generated holograms. Extensive Matlab code is integrated with the text throughout and available for download online, illustrating both theoretical results and practical considerations such as aliasing, zero padding and sampling. Accompanied by end-of-chapter problems and an online solutions manual for instructors, this is an indispensable resource for students, researchers and engineers in the fields of optical image processing a

The Third Edition of Understanding and Managing Vision Deficits is the go-to resource that will enable occupational therapists to develop a comprehensive understanding of vision, appreciate the various effects vision problems can have on the practice of occupational therapy, and to more effectively manage patients with vision disorders. Understanding and Managing Vision Deficits: A Guide for Occupational Therapists, Third Edition is a unique collaboration from occupational therapists, optometrists, and low vision rehabilitation specialists. Dr. Mitchell Scheiman presents a unique Three Component Model of Vision that includes: Visual integrity: Includes visual acuity (clarity), the optics of the eye, and eye health Visual efficiency skills: Includes focusing, eye teaming, and eye movements Visual information processing skills: Includes the ability to analyze, interpret and respond to visual information A major emphasis of the new edition is on management of eye move

●ACTIONABLE AND MEASURABLE LEARNING OBJECTIVES EMPHASIZE IMPORTANT CONCEPTS. Newly added learning objectives guide students through the edition, calling attention to critical key points.●SOLID OVERVIEW PRESENTS BREADTH OF COMPUTER SCIENCE WITHOUT PROGRAMMING LANGUAGE SPECIFICS. The authors expertly present a language-independent, breadth-first introduction to computer science that includes coverage of today's hardware, software, and applications as well as a modern view of ethics.●UNIQUE APPROACH INTEGRATES TOPICS USING THE CONCEPT OF ALGORITHMS. Rather than simply present a large collection of seemingly random and unrelated topics, the authors tie the discipline of computer science together using a six-layer hierarchy that clearly demonstrates how the subjects in the book relate to each other. Student gain a clear understanding of the entire discipline of computer science that prepares them for future study in this field.●EXTENSIVE EXERCISES AND PROBLEMS PROVIDE NUMEROUS OPPORTUNITIES

Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.This book provides a comprehensive introduction to the basic concepts, models, and applications of network representation learning (NRL). The book starts with an introduction to the background and rising of network embeddings as a general overview for readers. Then it introduces the development of NE techniques by presenting se

Learn the intricate workings of DAX and the mechanics that are necessary to solve advanced Power BI challenges. This book is all about DAX (Data Analysis Expressions), the formula language used in Power BI―Microsoft’s leading self-service business intelligence application―and covers other products such as PowerPivot and SQL Server Analysis Services Tabular. You will learn how to leverage the advanced applications of DAX to solve complex tasks.Often a task seems complex due to a lack of understanding, or a misunderstanding of core principles, and how certain components interact with each other. The authors of this book use solutions and examples to teach you how to solve complex problems. They explain the intricate workings of important concepts such as Filter Context and Context Transition. You will learn how Power BI, through combining DAX building blocks (such as measures, table filtering, and data lineage), can yield extraordinary analytical power. Throughout Pro Dax with Power BI t

人工智能作為國家產業轉型升級的重點領域，需要高層次技術技能人才。教育部增設人工智能技術應用、人工智能工程技術等專業，旨在培養理想信念堅定、德智體美勞全面發展、具有較高的科學文化水平、良好的人文素養、職業道德和精益求精工匠精神、掌握較為系統的基礎理論知識和技術技能、有較強的就業能力和可持續發展能力的人才。本書的編寫正是基於這樣一個人才培養目標，從技能出發、以技術為基礎、重在應用。本書共12個單元，主要內容：緒論、分詞和字典、數據預處理、語言模型和算法流程、感知機、條件隨機場、命名實體識別、信息抽取、文本聚類、文本分類、依存句法分析和深度學習與自然語言處理，每個單元包括若干個應用實踐。自然語言處理(Natural Language Processing，NLP)是計算機科學領域與人工智能領域中的一個重要方向，它研究能夠實現人與計算機之間用自然語言進行有效通信的各種理論和方法，涉及所有用計算機對自然語言進行的操作，是人工智能技術技能人才必須掌握的內容。本書適合高等職業院校、應用型本科院校作為自然語言處理課程的教學與實訓教材，也可供人工智能從業者作為理論與實踐結合的參考書。

不會艱深晦澀、不再高深莫測 你一定能看懂的自然語言處理入門書！ INTRODUCTION TO NATURAL LANGUAGE PROCESSING ♘Java與Python雙實作：圖文並茂！演算法、數學公式、程式碼相輔相成。 ♘探索式學習路徑：循序漸進！從問題、演算法再到範例實作，一目瞭然。 編輯推薦 作者匯集多年經驗，從基本概念出發，逐步介紹中文分詞、詞性標註、命名實體識別、資訊抽取、文字聚類、文字分類、句法分析這幾個熱門問題的演算法原理與工程實作。透過講解多種演算法，比較它們的優缺點與適用場景，同時詳細展示實際專案導向的程式碼，協助讀者真正將自然語言處理（NLP）應用到正式環境之中。 儘管作者目前是NLP領域的翹楚，但他曾是非本科生，對自學入門有親身體驗，深諳初學者的學習痛點。希望透過這本與眾不同的入門讀物，為讀者打開另一扇機會之門，幫助你零起點上手NLP，讓你在通勤時也能把書讀完讀懂！ 隨著本書的學習，你將從普通程式設計師晉級為機器學習工程師，最後進化為NLP工程師。 專家好評 HanLP作者何晗寫的這本書值得一讀。這本書系統性地介紹NLP的基礎技術，深入淺出、容易理解，對初學者助益極大。 周明 微軟亞洲研究院副院長，國際計算語言學會會長 本書不僅介紹NLP的任務及演算法，也提供可以實際執行的線上程式碼，非常適合NLP初學者入門並快速部署到正式環境。 王斌 小米人工智慧實驗室主任、NLP首席科學家

【本書特色】 最貼近新手的深度學習理論及應用全方位入門書！ ✪學習必備理論，打好基礎，新手不怕被過多的數學式嚇跑。 ✪使用PyTorch直覺易懂且強大的深度學習框架，開始應用的第一步。 ✪了解自然語言處理、電腦視覺與強化學習等三大領域經典應用與實作，領略深度學習的強大。 ✪兼顧理論與實作，而非偏頗一方，培養讀者較全面的理解。 ✪包含經典學術論文與知名專案技術講解，幫助讀者掌握此技術所能到達的高度。 ✪每章末提供自我檢驗題目，幫助理解與統整各章概念。 【內容簡介】 本書內容改編自第12屆iT邦幫忙鐵人賽AI & Data組冠軍系列文章《Knock Knock！Deep Learning》，是專為深度學習初學者所規劃的內容，旨在以淺顯易懂的文字，帶領深度學習領域的新手度過入門撞牆期。內容從深度學習的基本理論開始，並以PyTorch框架的介紹過渡至應用篇，最後以自然語言處理、電腦視覺與強化學習等三大領域的經典論文與實作專案收尾，循序漸進且去蕪存菁。本書會帶入許多故事性的敘述和插圖，結合作者自身在史丹佛大學修讀碩士期間的學習心得，以及深度學習發展相關的故事，期使本書讀起來不會如教科書一樣厚重，亦不會像網路上的技術文章一般零散無脈絡，讓讀者對深度學習領域的發展有一定的概念。 【內容重點】 ✪了解深度學習的基礎理論以及必備的實作知識與工具 內容從人類的神經網路開始，介紹深度學習與其相似之處，並理解神經網路的學習步驟，同時也介紹一些必備的實作知識與工具，以具備基本的實作工程技能。 ✪入門深度學習框架PyTorch 內容介紹語法簡潔、好上手且在學術界流行的PyTorch框架，著重實作與應用。 ✪深度學習×自然語言處理×電腦視覺×強化學習 內容會依序談到深度學習在三方面的應用，如自然語言處理（Natural Language Processing，NLP )、電腦視覺（Computer Vision，CV )、強化學習（Reinforcement Learning，RL )。除了基本簡介外，還會介紹一些基本實作和改變世界的技術成果。 【適用讀者】 ✪對深度學習有興趣，但還不知道它是什麼、能做什麼的新手。 ✪零散讀過深度學習相關文章，但仍有知識缺口的入門者。 ✪被教科書中龐大的數學理論嚇到，而對深度學習卻步的讀者。 ✪正在上學校的深度學習課程，但不知道實作從何開始的學生。